Announcements of Opportunity
SURF: Announcements of Opportunity
Below are Announcements of Opportunity posted by Caltech faculty and JPL technical staff for the SURF program. Each AO indicates whether or not it is open to non-Caltech students. If an AO is NOT open to non-Caltech students, please DO NOT contact the mentor. Announcements of Opportunity are posted as they are received. Please check back regularly for new AO submissions!
Remember: This is just one way that you can go about identifying a suitable project and/or mentor. Click here for more tips on finding a mentor. Announcements for external summer programs are listed here.
*Students applying for JPL projects should complete a SURF@JPL application instead of a "regular" SURF application.
*Students pursuing opportunities at JPL must be U.S. citizens or U.S. permanent residents.
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Project: | Earthquake Time-Series Analysis and Synthesis using Machine Learning | ||||||||
Disciplines: | Civil Engineering, Data Science, Geophysics, Computer Science | ||||||||
Mentor: |
Domniki Asimaki,
Professor of Mechanical and Civil Engineering, (EAS),
domniki@caltech.edu, |
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Mentor URL: | https://www.asimaki.caltech.edu (opens in new window) | ||||||||
Background: |
Seismic hazard is quantified using ground motion measurements from past earthquakes. These measurements are used to develop statistical models that engineers and earth scientists then use to estimate ground motion shaking of future earthquakes. Recently, earth scientists are running simulations of future large events (i.e. The Big One) that are not included in the recorded databases. These simulations, however, are limited by the coarseness of their input parameters. In this project, we are using machine learning to fuse simulations with observations. |
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Description: | The student will be developing machine learning algorithms to extract high frequency features from observed ground motion signals and fusing them with simulated long period motions. Alternatively, the student will be developing machine learning algorithms to translate response spectra into Fourier spectra, intended for engineering applications of the fused ground motions in engineering practice; or developing algorithms to signal process raw observed ground motions into processed ground motions for engineering applications. | ||||||||
References: |
https://arxiv.org/abs/2309.03447 https://openreview.net/pdf?id=j3oQF9coJd |
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Student Requirements: |
Signal processing Machine learning Python |
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Programs: |
This AO can be done under the following programs:
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